Speech processing provides a compelling need for more computing power, and is important in making the PC (personal computer) more accessible and productive. Any speech engine has a process for recognizing human speech and turning it into something the computer understands. In effect, the computer needs a translator. Every speech engine uses many operations to listen to and understand human speech. Some of these are described below:                Word separation is the process of creating discreet portions of human speech. Each portion can be as large as a phrase or as small as a single syllable or word part.        Vocabulary is a list of speech items that the speech engine can identify.        Word matching is a method that the speech engine uses to look up a speech part in the systems' vocabulary—the search engine portion of the system.        Speaker dependence is the degree to which the speech engine is dependent on the vocal tones and speaking patterns of individuals.        Grammar rules are used by speech recognition (SR) software to analyze human speech input, and in the process, attempt to understand what a person is saying.        
When writing speech processing applications, many types of grammars can be used. Grammars can be divided into three types. Dictation grammars use the context in which words are spoken to enable a speech engine to recognize words from a dictation vocabulary provided with the speech engine. Dictation grammars are typically used in applications that allow users to dictate freely into an edit control. Limited domain grammars are useful in situations where the vocabulary of a system need not be very large. Examples include systems that use natural language to accept command statement.
Rule-based grammars, such as context-free grammars (hereinafter “CFG”), on the other hand, use rules to determine what the speech engine recognizes. In a CFG, a grammar text file contains rules defining the patterns and combinations of words and phrases that the speech engine will recognize when users speak them. While CFGs offer a great degree of flexibility when interpreting human speech, a particular CFGs accuracy is limited to the words, rules, and lists defined for the CFG, as the grammar must be completely specified prior to or during runtime. As a result, CFGs currently cannot be used for specifying arbitrary words. While dictation grammars can be used to specify arbitrary words, the tradeoff is that dictation grammars consume more CPU (central processing unit) power.